NC commuter rail ridership & market study summary report - Page 9

NCRR Commuter Rail Ridership & Market Study
6
portion of the study corridor between the southeast edge of the TRM and the western edge of the
GTDM that is not covered by any of the existing models.
Since all three of the existing forecasting model systems are TransCAD-based four-step urban travel
demand models, we chose to take advantage of the MPOs’ efforts in developing and validating models
that accurately represent their local travel patterns. Accordingly, we combined the three models to
form the core of our corridor-wide travel demand model system, and supplemented the combined
models with data for the area between the southeastern edge of the TRM and the western edge of the
GTDM. Figure 4.1 below shows the coverage of each of the existing models in addition to the area
filled in by SDG. Note that while our model does take into account travel patterns in the Winston-
Salem and High Point areas, it does not include commuter rail service west of Greensboro, as it is
outside the scope of this study.
FIGURE 4.1 MODEL COMPOSITION AND COVERAGE
WAKE
GUILFORD
FORSYTH
DURHAM
DAVIDSON
PITT
CABARRUS
ALAMANCE
RANDOLPH
ROWAN
JOHNSTON
ORANGE
WAYNE
ROCKINGHAM
HARNETT
NASH
MOORE
WILSON
LENOIR
STANLY
HALIFAX
EDGECOMBE
CHATHAM
LEE
GRANVILLE
FRANKLIN
STOKES
VANCE
PERSON
DAVIE
MONTGOMERY
CASWELL
NORTHAMPTON
WARREN
GREENE
Model preparation
Since the TRM covers the majority of the large population and employment centers in the study area,
we chose to base our corridor forecasting model on the general model structure of the TRM, and
modify the inputs for the PTRM and GTDM to conform to the TRM inputs. The models have different
ways of treating many inputs, and incorporate different assumptions and procedures. When combining
the models, it was necessary to make decisions regarding the conversion of attributes between model
systems to resolve these differences. The key model components combined included the following:
I Traffic analysis zones (TAZs): Travel demand models typically divide a study area into
traffic analysis zones (TAZs), which are relatively small geographic areas that have uniform
characteristics and represent locations where trips begin or end. The final SDG corridor
model includes more than 4,300 TAZs, which is a very large number for a model of this
type. This high level of detail causes the model to be very computationally intensive.

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NCRR Commuter Rail Ridership & Market Study
6
portion of the study corridor between the southeast edge of the TRM and the western edge of the
GTDM that is not covered by any of the existing models.
Since all three of the existing forecasting model systems are TransCAD-based four-step urban travel
demand models, we chose to take advantage of the MPOs’ efforts in developing and validating models
that accurately represent their local travel patterns. Accordingly, we combined the three models to
form the core of our corridor-wide travel demand model system, and supplemented the combined
models with data for the area between the southeastern edge of the TRM and the western edge of the
GTDM. Figure 4.1 below shows the coverage of each of the existing models in addition to the area
filled in by SDG. Note that while our model does take into account travel patterns in the Winston-
Salem and High Point areas, it does not include commuter rail service west of Greensboro, as it is
outside the scope of this study.
FIGURE 4.1 MODEL COMPOSITION AND COVERAGE
WAKE
GUILFORD
FORSYTH
DURHAM
DAVIDSON
PITT
CABARRUS
ALAMANCE
RANDOLPH
ROWAN
JOHNSTON
ORANGE
WAYNE
ROCKINGHAM
HARNETT
NASH
MOORE
WILSON
LENOIR
STANLY
HALIFAX
EDGECOMBE
CHATHAM
LEE
GRANVILLE
FRANKLIN
STOKES
VANCE
PERSON
DAVIE
MONTGOMERY
CASWELL
NORTHAMPTON
WARREN
GREENE
Model preparation
Since the TRM covers the majority of the large population and employment centers in the study area,
we chose to base our corridor forecasting model on the general model structure of the TRM, and
modify the inputs for the PTRM and GTDM to conform to the TRM inputs. The models have different
ways of treating many inputs, and incorporate different assumptions and procedures. When combining
the models, it was necessary to make decisions regarding the conversion of attributes between model
systems to resolve these differences. The key model components combined included the following:
I Traffic analysis zones (TAZs): Travel demand models typically divide a study area into
traffic analysis zones (TAZs), which are relatively small geographic areas that have uniform
characteristics and represent locations where trips begin or end. The final SDG corridor
model includes more than 4,300 TAZs, which is a very large number for a model of this
type. This high level of detail causes the model to be very computationally intensive.